AI for developers has moved from autocomplete to agents that can plan, write, test, and review code across a whole repository. Tools such as GitHub Copilot, Cursor, Claude Code, and OpenAI Codex now handle much of the routine implementation, while developers focus on design, review, and ownership of what ships. The teams that benefit most pair AI speed with strong testing and code review.
Part of our AI Use Cases. Last updated September 2026.
AI for Developers: Guides
| Guide | What It Covers |
|---|---|
| Software development | Coding agents, pair programming, refactoring |
| Testing | Generating and maintaining tests |
| Documentation | Docs, comments, and API references |
| Deployment | CI/CD, infrastructure, and incidents |
The Core Tools
- GitHub Copilot: AI in your existing editor and GitHub workflow; usage-based billing since June 2026.
- Cursor: an AI-first editor with a project-wide agent.
- Claude Code: agentic coding in the terminal and IDE, included with Claude paid plans.
- OpenAI Codex: delegate coding tasks to an agent with ChatGPT paid plans.
Compare them in Cursor vs GitHub Copilot and AI Coding Tools.
Practices That Keep AI-Written Code Safe
- Review every change as you would a colleague’s.
- Keep tests strong; they are your safety net for AI changes.
- Protect secrets and proprietary code with business plans and privacy settings.
- Watch dependencies; AI may suggest packages that are outdated or do not exist.
- Track costs as agent usage is increasingly metered.
Frequently Asked Questions
Will AI replace software developers?
AI is changing the job toward design, review, and orchestration. Developers who use AI well are more productive; responsibility for software remains human.
Which AI coding tool should I start with?
If you want to keep your editor, try GitHub Copilot or Claude Code. If you want an AI-first editor, try Cursor.
Is AI-generated code secure?
Not automatically. Review and test it, especially authentication, data handling, and dependencies.